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submit_request

Ask for a change in plain English: a feature, a bug fix, or a new direction.

Submit ONE feature or intent per call; split a multi-feature ask into
separate requests. `text` must be under 16000 characters. Returns
{thread_id, status, next_action, poll_after_seconds, next_step}; follow
next_step (re-check get_request_status after poll_after_seconds).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
project_idYes
workflow_profileNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / workflow_profile
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "title": "Workflow Profile"
      +}
  2. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (not read-only, not idempotent, not destructive), the description discloses asynchronous behavior: it returns a thread_id, status, next_action, poll_after_seconds, and next_step, and instructs the agent to poll get_request_status. This adds meaningful operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: purpose, cardinality constraint, text limit, and return behavior are each stated in a few sentences with no filler. The use of backticks for parameter names and a clear next-step instruction keeps it scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a submission tool with a provided output schema, the description covers the key usage loop, polling behavior, and limits, making it actionable. The main gap is the unexplained workflow_profile parameter, which keeps it from being fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates for the text parameter by defining its format, scope, and length limit, but it does not explain project_id or workflow_profile. The required project_id is only self-evident from its name, and workflow_profile is left undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Ask for a change') and the resource/domain (feature, bug fix, new direction) with clear intent. It does not explicitly differentiate from sibling refine_request or answer_request, but the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides concrete usage constraints: one feature/intent per call, splitting multi-feature asks, a 16000-character text limit, and explicit follow-up steps via get_request_status. It lacks explicit 'do not use when...' exclusions, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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